Personalized Modeling of Travel Behaviors and Traffic Dynamics
Journal article, 2022

Emerging mobile Internet applications have become valuable data sources for fine-grained transportation analysis, which allows the introduction of the concept of Personalization in both microscopic and macroscopic modeling of travel behaviors and traffic dynamics. Inspired by personalized recommendation systems, the personalized transportation models emphasize the importance of individual and local information. Two representative cases are presented in this study and two architectures, namely the travel behavior modeling architecture and the geoinformation modeling architecture, are proposed to address the problems of bike-sharing destination prediction and ensemble of ride-hailing demand predictors, respectively. Their performance has been verified by two case studies using the Mobike bike-sharing data and the DiDi ride-hailing demand data.

Author

Cheng Lyu

Technical University of Munich

Yang Liu

Transportgruppen

Liang Wang

Ministry of Transport

Xiaobo Qu

Transportgruppen

Journal of Transportation Engineering Part A: Systems

24732907 (ISSN) 24732893 (eISSN)

Vol. 148 10 04022081

Subject Categories

Computer Engineering

Transport Systems and Logistics

Computer Systems

DOI

10.1061/JTEPBS.0000740

More information

Latest update

1/3/2024 9